Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "73"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 73 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 29 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 27 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 73, Node N05:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459846 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 24.030311 -1.035895 33.364030 -0.539875 21.448598 0.380253 5.623196 -0.115973 0.0275 0.0612 0.0256 1.188424 1.214198
2459844 digital_ok 100.00% 100.00% 100.00% 0.00% - - 15.567953 0.846542 4.957166 -0.218120 3.618700 1.052709 12.533094 1.597940 0.0239 0.0243 0.0005 nan nan
2459840 digital_ok 0.00% 100.00% 100.00% 0.00% - - 3.610704 3.074700 -1.083308 -1.316501 1.232822 1.675584 1.199968 0.737452 0.0232 0.0239 0.0010 nan nan
2459839 digital_ok 0.00% - - - - - 0.294263 0.219327 -0.723446 -0.654885 -0.534830 -0.851238 1.157775 0.748276 nan nan nan nan nan
2459838 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 15.593429 1.587315 21.959191 -0.878938 19.574674 0.398915 0.580705 -0.074561 0.0373 0.6886 0.3818 0.000000 0.000000
2459836 digital_ok - 100.00% 100.00% 0.00% - - nan nan nan nan nan nan nan nan 0.0315 0.0348 0.0027 nan nan
2459835 digital_ok 100.00% 100.00% 100.00% 0.00% - - 2.424388 -0.925550 2.173977 -0.880037 0.591320 2.207272 1.557881 6.285234 0.0330 0.0364 0.0021 nan nan
2459833 digital_ok 100.00% 100.00% 100.00% 0.00% - - 6.466209 0.137042 2.635838 0.333032 7.186896 11.768199 3.609207 2.358771 0.0256 0.0275 0.0036 nan nan
2459832 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 29.718369 -0.594454 24.653983 0.296471 13.593285 0.590908 1.313026 0.896144 0.0342 0.5270 0.3302 1.192571 2.751203
2459831 digital_ok 0.00% 100.00% 100.00% 0.00% - - 0.120856 -0.225008 -0.229677 -0.136401 0.739007 2.479249 1.012555 0.703970 0.0257 0.0335 0.0029 nan nan
2459830 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 30.055037 -0.024816 35.214341 0.987785 39.730666 -0.218043 3.499208 0.861380 0.0317 0.5162 0.2804 1.177536 2.819479
2459829 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 26.813804 1.441966 28.680898 0.250282 28.597988 15.644194 4.525425 3.182383 0.0346 0.6423 0.3698 0.000000 0.000000
2459828 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 25.486553 0.308492 30.939032 3.305048 36.565384 2.291144 9.012941 -1.773532 0.0369 0.5479 0.3037 1.124267 3.976304
2459827 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 22.139982 0.336987 34.735896 5.214357 24.525605 1.635140 0.204597 -0.107667 0.0352 0.6611 0.3426 1.209018 4.822102
2459826 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 24.062087 -0.150438 39.048206 3.721807 48.821368 2.471402 5.377118 -0.294839 0.0357 0.5809 0.2859 0.000000 0.000000
2459825 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 26.482550 -0.406859 31.070433 1.734249 27.549250 0.535219 0.008725 -0.439043 0.0346 0.5775 0.2374 1.322048 4.408842
2459824 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 14.487537 1.596627 24.703633 2.257002 10.648017 -0.290968 1.400649 -0.094360 0.0344 0.7090 0.2992 1.241069 9.654327
2459823 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 25.179339 0.478329 46.463214 2.124980 34.197772 0.255078 25.600294 0.139449 0.0332 0.6185 0.2762 -0.000000 -0.000000
2459822 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 24.452221 0.281384 42.578167 2.451166 30.794583 0.993050 0.687979 -0.861425 0.0329 0.6070 0.2575 1.205376 3.293573
2459821 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 27.290621 0.228633 43.572254 2.940935 26.205350 0.767154 -1.257721 -0.039447 0.0324 0.6390 0.3141 1.191407 3.171066
2459820 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 21.569247 -0.029863 34.830515 2.918230 66.185640 2.085101 2.788263 0.059962 0.0434 0.6949 0.3643 1.225085 3.808817
2459817 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 24.275565 0.013344 42.317071 1.017455 36.206731 0.859834 1.014506 -0.669551 0.0376 0.6919 0.3676 1.195348 2.724568
2459816 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 18.239146 -0.696655 42.351710 0.158921 46.582541 0.956424 4.923122 1.705398 0.0374 0.6115 0.3620 1.226511 3.269667
2459815 digital_ok 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 21.974665 0.379776 46.318158 -0.409018 47.499492 0.392475 8.381601 2.695237 0.0336 0.6932 0.4024 1.183698 2.968552
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 73: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Power 33.364030 24.030311 -1.035895 33.364030 -0.539875 21.448598 0.380253 5.623196 -0.115973

Antenna 73: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Shape 15.567953 15.567953 0.846542 4.957166 -0.218120 3.618700 1.052709 12.533094 1.597940

Antenna 73: 2459840

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Shape 3.610704 3.610704 3.074700 -1.083308 -1.316501 1.232822 1.675584 1.199968 0.737452

Antenna 73: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Temporal Discontinuties 1.157775 0.219327 0.294263 -0.654885 -0.723446 -0.851238 -0.534830 0.748276 1.157775

Antenna 73: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Power 21.959191 1.587315 15.593429 -0.878938 21.959191 0.398915 19.574674 -0.074561 0.580705

Antenna 73: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok nn Temporal Discontinuties 6.285234 -0.925550 2.424388 -0.880037 2.173977 2.207272 0.591320 6.285234 1.557881

Antenna 73: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok nn Temporal Variability 11.768199 0.137042 6.466209 0.333032 2.635838 11.768199 7.186896 2.358771 3.609207

Antenna 73: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Shape 29.718369 29.718369 -0.594454 24.653983 0.296471 13.593285 0.590908 1.313026 0.896144

Antenna 73: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
73 N05 digital_ok nn Temporal Variability 2.479249 0.120856 -0.225008 -0.229677 -0.136401 0.739007 2.479249 1.012555 0.703970

Antenna 73: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Temporal Variability 39.730666 30.055037 -0.024816 35.214341 0.987785 39.730666 -0.218043 3.499208 0.861380

Antenna 73: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Power 28.680898 1.441966 26.813804 0.250282 28.680898 15.644194 28.597988 3.182383 4.525425

Antenna 73: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Temporal Variability 36.565384 0.308492 25.486553 3.305048 30.939032 2.291144 36.565384 -1.773532 9.012941

Antenna 73: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Power 34.735896 22.139982 0.336987 34.735896 5.214357 24.525605 1.635140 0.204597 -0.107667

Antenna 73: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Temporal Variability 48.821368 -0.150438 24.062087 3.721807 39.048206 2.471402 48.821368 -0.294839 5.377118

Antenna 73: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Power 31.070433 -0.406859 26.482550 1.734249 31.070433 0.535219 27.549250 -0.439043 0.008725

Antenna 73: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Power 24.703633 14.487537 1.596627 24.703633 2.257002 10.648017 -0.290968 1.400649 -0.094360

Antenna 73: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Power 46.463214 0.478329 25.179339 2.124980 46.463214 0.255078 34.197772 0.139449 25.600294

Antenna 73: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Power 42.578167 24.452221 0.281384 42.578167 2.451166 30.794583 0.993050 0.687979 -0.861425

Antenna 73: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Power 43.572254 0.228633 27.290621 2.940935 43.572254 0.767154 26.205350 -0.039447 -1.257721

Antenna 73: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Temporal Variability 66.185640 21.569247 -0.029863 34.830515 2.918230 66.185640 2.085101 2.788263 0.059962

Antenna 73: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Power 42.317071 24.275565 0.013344 42.317071 1.017455 36.206731 0.859834 1.014506 -0.669551

Antenna 73: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Temporal Variability 46.582541 -0.696655 18.239146 0.158921 42.351710 0.956424 46.582541 1.705398 4.923122

Antenna 73: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok ee Temporal Variability 47.499492 0.379776 21.974665 -0.409018 46.318158 0.392475 47.499492 2.695237 8.381601

Antenna 73: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 73: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
73 N05 digital_ok nn Shape nan nan nan inf inf nan nan nan nan
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